23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009

23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009

11 Lectures · Dec 7, 2009

About

You are invited to view the Twenty-Third Annual Conference on Neural Information Processing Systems, which is the premier scientific meeting on Neural Computation.

A one-day Tutorial Program offered a choice of six two-hour tutorials by leading scientists. The topics span a wide range of subjects including Neuroscience, Learning Algorithms and Theory, Bioinformatics, Image Processing, and Data Mining.

The NIPS Conference featured a single track program, with contributions from a large number of intellectual communities. Presentation topics included: Algorithms and Architectures; Applications; Brain Imaging; Cognitive Science and Artificial Intelligence; Control and Reinforcement Learning; Emerging Technologies; Learning Theory; Neuroscience; Speech and Signal Processing; and Visual Processing.

The Poster Sessions offered high-quality posters and an opportunity for researchers to share their work and exchange ideas in a collegial setting. The majority of contributions accepted at NIPS were presented as posters.

The Demonstrations enabled researchers to highlight scientific advances, systems, and technologies in ways that go beyond conventional poster presentations. It provided a unique forum for demonstrating advanced technologies — both hardware and software — and fostering the direct exchange of knowledge.

Detailed information can be found at NIPS 2009 Conference Homepage.


Click on the picture for the videos from 2009 NIPS Workshops. ||[[:nipsworkshops09_whistler]]||

Related categories

Uploaded videos:

Invited Talks

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01:06:03

Relative Entropy

Sergio Verdu

Jan 25, 2010

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Deep Learning with Multiplicative Interactions

Geoffrey E. Hinton

Jan 20, 2010

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The Rat Vibrissal Array as a Model Sensorimotor System

Mitra Hartmann

Jan 19, 2010

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54:57

Learning and Inference in Low-Level Vision

Yair Weiss

Jan 19, 2010

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Bayesian Analysis of Markov Chains

Persi Diaconis

Jan 19, 2010

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Tutorials

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01:59:35

Making Very Large-Scale Linear Algebraic Computations Possible Via Randomization

Gunnar Martinsson

Jan 19, 2010

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8763 Views

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01:56:32

Understanding Visual Scenes

Antonio Torralba

Jan 19, 2010

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28277 Views

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01:54:56

Model-Based Reinforcement Learning

Michael Littman

Jan 19, 2010

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24616 Views

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02:00:44

Sparse Methods for Machine Learning: Theory and Algorithms

Francis R. Bach

Jan 19, 2010

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36817 Views

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01:46:01

Deep Learning in Natural Language Processing

Jason Weston,

Ronan Collobert

Jan 19, 2010

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29960 Views

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01:45:26

Sequential Monte-Carlo Methods

Arnaud Doucet,

Nando de Freitas

Jan 19, 2010

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43645 Views

Tutorial